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Devis TuiaView profile

Associate Professor

• Earth Observation
• Remote Sensing
• Machine Learning
• +5 more

Devis Tuia serves as Associate Professor at the Swiss Federal Institute of Technology Lausanne (EPFL), holding appointments in the Institute of Environmental Engineering (IIE) within the School of Architecture, Civil and Environmental Engineering (ENAC). He leads the Environmental Computational Science and Earth Observation Laboratory (ECEO) since 2020 and contributes to EPFL's Doctoral Program in Civil and Environmental Engineering. His academic journey began in Lausanne with studies at UNIL and EPFL, culminating in a PhD in remote sensing from UNIL. Postdoctoral research followed at institutions in Valencia, Boulder, and EPFL, focusing on machine learning model adaptation. He progressed from Research Assistant Professor at University of Zurich to Associate and Full Professor at Wageningen University before joining EPFL. Tuia's research bridges Earth observation with artificial intelligence, specializing in interpretable deep learning for environmental applications. His lab develops algorithms for making remote sensing accessible, with particular emphasis on digital wildlife conservation through automated censuses using drone and satellite imagery. Current projects tackle the 'black box' problem in environmental modeling while advancing spatial intelligence for sustainable urban development. His 2023-2025 publication portfolio reveals three dominant trends: (1) species distribution modeling using incomplete observations, (2) multimodal fusion of satellite/drone data with textual descriptions, and (3) interpretable AI frameworks for environmental decision-making. This work consistently addresses real-world challenges like wildfire forecasting and biodiversity monitoring. As an educator, Tuia supervises 12 current PhD students and has graduated 4 former EPFL doctoral candidates. His teaching portfolio includes Frontiers of Deep Learning for Engineers , Sensing and Spatial Modeling for Earth Observation , and Image Processing for Earth Observation courses. The ECEO laboratory maintains active collaborations with ESA-NASA initiatives and conservation organizations globally.

Antonio GonzálezView profile

Professor

• Computer Architecture
• Microarchitecture
• Compilers
• +7 more

Antonio González is a full Professor at the Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC), where he is affiliated with the Department of Computer Architecture. He leads the Microarchitecture and Compilers (ARCO) research group, focusing on robust and energy-efficient computing systems, including general-purpose processors, GPUs, and cognitive computing architectures. His research spans computer architecture, microarchitecture, compilers, GPU design, and deep learning acceleration, with a strong emphasis on energy efficiency and memory optimization. His work integrates hardware and compiler techniques to enhance performance in modern computing systems. The recent publications highlight a strong trend in energy-efficient DNN acceleration, GPU microarchitecture, memory systems, and near-data processing. His team explores novel quantization methods, adaptive caching, and architectural extensions for vision and AI workloads, published in top-tier venues such as MICRO, ISCA, and IEEE/ACM journals. ACM Fellow (2020) ICREA Academia Award (2014, 2019, 2024) UPC Duran Farell Award (2008) HiPEAC 2024 Paper Award (twice) González has supervised several PhD students and leads competitive R&D+i projects, including those funded by ICREA and the European Research Council. His research group collaborates extensively within UPC and with international institutions. He is actively involved in advancing computer architecture through innovation in simulation, hardware design, and AI acceleration. He is a member of IEEE and ACM, and his work continues to influence both academic and industrial developments in high-performance and energy-efficient computing.

Manuel KaufmannView profile

Lecturer

• 3D Human Motion Capture
• Computer Vision
• Sensor Data Processing
• +3 more

Manuel Kaufmann is a Lecturer in the Department of Computer Science at ETH Zürich. His work focuses on advanced 3D human motion capture, sensor-based systems, and computer vision applications. He is affiliated with the Institute of Informatics (inf.ethz.ch) and contributes to research in real-time motion tracking, dataset development, and machine learning integration for human-robot interaction. Research interests include holistic human-scene reconstruction from monocular videos, gaze estimation using EEG signals, and expressive avatar creation. His projects emphasize practical applications in robotics, sports analytics, and biomedical engineering, often leveraging electromagnetic and inertial sensors for high-precision data acquisition. His publications reflect a trend toward multi-modal data fusion, real-world dataset creation (e.g., WorldPose, ARCTIC), and addressing challenges in loose garment modeling (Reloo). These efforts aim to improve markerless motion capture, crowd analysis, and human-robot collaboration. No scientific awards or grants are explicitly listed. He has no documented advisees, though his research may involve collaborations with students or teams. His office is located at OAT X 23, Andreasstrasse 5, Zürich, Switzerland, and contact details include a phone number and professional email.

Clay CórdovaView profile

Associate Professor

• Theoretical Physics
• Quantum Field Theory
• Particle Physics
• +3 more

Clay Córdova is an Associate Professor at the University of Chicago, associated with the Enrico Fermi Institute, James Franck Institute, Kadanoff Center, and Kavli Institute. His research focuses on theoretical physics, particularly quantum field theory, non-invertible symmetries, and their applications in particle and condensed matter physics. Córdova’s work explores topological phases, gauge theories, and string theory, with recent contributions to non-invertible symmetry classification and their role in phase transitions. His research interests include categorical symmetries, topological defects, and anomaly matching in quantum field theories. He has pioneered studies on soliton-particle degeneracies, anyon condensation mechanisms, and anomalies in non-invertible symmetry frameworks. Córdova’s work bridges high-energy physics with condensed matter systems, often employing advanced mathematical techniques from category theory and algebraic topology. His 2023 Sloan Research Fellowship highlights recognition of his contributions. Key research trends span non-invertible symmetries across dimensions, topological field theory applications, and interdisciplinary methods combining machine learning with lattice gauge theory. Current projects include exploring duality defects, gapped phase obstructions, and symmetry-enriched phases in (3+1)D systems.

Julie RakView profile

Professor

• Life Writing
• Autobiography
• Diaries and Journals
• +9 more

Julie Rak is the HM Tory Chair and Professor in the Department of English and Film Studies at the University of Alberta. She holds a BA and PhD from McMaster University and an MA from Carleton University. Her research focuses on auto/biography, life writing, and nonfiction in North America, with specialties in gender, Canadian literature, and publishing studies. She has authored or co-edited numerous books, including False Summit: Gender in Mountaineering Nonfiction (2021) and The Routledge Introduction to Auto/biography in Canada (2023). Rak’s academic roles include interim Chair of the EFS Department (2023–2024) and leadership in the Stories of Change research group. She has received prestigious awards such as the J. Gordin Kaplan Award (2023) and the Killam Annual Professorship (2017–2018). Her research explores marginalized narratives, including Inuit literature and digital life writing, with a commitment to inclusivity and community engagement. Her teaching spans undergraduate and graduate courses on autobiography, gender theory, and Canadian literature. She actively supervises research projects and supports student initiatives like the Roger Smith Undergraduate Research Award. Rak’s work bridges academic rigor with public scholarship, with over 90 media engagements. Education: PhD in English, McMaster University MA in Canadian Studies, Carleton University BA in English, McMaster University Grants & Projects: SSHRC Insight Grant for Government Agents, Literary Agents: Inuit Books and Government Intervention, 1968–1985 Leadership in the Stories of Change initiative Awards & Honors: Fellow of the Royal Society of Canada (2022) Henry Marshall Tory Chair (2019–2025) 2024 Visiting Professor at Merton College, Oxford

Sherry B. OrtnerView profile

Research Professor

• Cultural Anthropology
• Feminist Theory
• Media Studies
• +3 more

Sherry B. Ortner is a Distinguished Research Professor of Anthropology at UCLA, specializing in cultural and social theory, feminist theory, and media studies. She holds degrees from Bryn Mawr College (A.B.), University of Chicago (M.A., Ph.D.). Her research spans Sherpa ethnography in Nepal, U.S. social class dynamics, and independent film critique. She has been awarded the J.I. Staley Prize, Retzius Medal, and MacArthur Fellowship. Ortner’s work interrogates late capitalism, neoliberalism, and cultural production, particularly through independent film movements. Her shift from Himalayan studies to U.S. cultural analysis reflects a focus on global and local power structures. She has held academic positions at Berkeley, Columbia, and the University of Michigan before joining UCLA in 2004. Key Research Themes : Feminist theory, media anthropology, class and capitalism, cultural critique. Awards : American Academy of Arts and Sciences membership, Guggenheim and NEH fellowships. Her publications include Not Hollywood (2013), New Jersey Dreaming (2003), and Life and Death on Mt. Everest (2000). Ortner’s recent work critiques patriarchal structures and neoliberalism’s cultural impacts. She is a foundational voice in contemporary anthropological theory.

Oscar P. BrunoView profile

Professor

• Partial Differential Equations
• Computational Science
• Numerical Analysis
• +5 more

Oscar P. Bruno is a Professor of Applied and Computational Mathematics at the California Institute of Technology (Caltech). He holds a Licenciado from the University of Buenos Aires (1982) and a Ph.D. in Mathematics from New York University's Courant Institute (1989). Since 1998, he has been a Professor at Caltech, previously serving as Associate Professor (1995–98) and Executive Officer for Applied Mathematics (1998–2000). His research focuses on developing high-performance numerical methods for solving partial differential equations (PDEs), addressing challenges in complex geometries, singularities, and high-frequency phenomena. Key contributions include the Fourier Continuation (FC) method and integral-equation techniques, enabling solutions to previously intractable PDE problems in science and engineering. Prof. Bruno's expertise spans computational electromagnetics, computational fluid dynamics (CFD), solid mechanics, and mathematical physics. His work integrates numerical analysis, multiphysics modeling, and computational science to solve real-world problems in geophysics, optics, and fluid dynamics. He has received numerous awards, including membership in the National Academy of Sciences of Argentina (2020), the Vannevar Bush National Security Science and Engineering Fellowship (2016), and SIAM Fellow (2013). Bruno serves on editorial boards for journals like SIAM Journal on Scientific Computing and SIAM Journal on Applied Mathematics, and participates in national science advisory roles. His teaching includes advanced courses on applied mathematics methods (ACM/IDS 101 ab), emphasizing theoretical foundations and numerical techniques for PDEs. His research group develops cutting-edge solvers with applications in shock dynamics, optical tomography, and geophysical fluid dynamics.

Yintan FanView profile

Lecturer

• Economic Sociology
• Sociology of Work
• Migration Studies
• +4 more

Yintan Fan is an Assistant Lecturer and Postgraduate Research Student in the Department of Sociology and Criminology at the University of Essex. His current PhD research focuses on ethnic entrepreneurship and chambers of commerce, exploring how migrant organizations influence socio-economic dynamics. Previously, he worked as a university lecturer (2019–2022), market researcher (2016–2019), and journalist (2009–2011). Education includes a BA in Sociology from Jiangnan University (2012), an MA in Social Science from Complutense University of Madrid (2016), and an MA in Sociology from Bielefeld University (2017). He holds certifications in teaching (HEA Fellowship, China), translation (fluent in Chinese, English, German, Spanish), and project management. Research interests span Economic Sociology , Sociology of Work , Migration Studies , and Cultural Sociology . His work examines topics such as Chinese students' social adaptation in Germany, ethnic entrepreneurs in Spain and Italy, and labor rights in China. Key outputs include conference presentations on migrant organizations, global fashion industries, and trade union efficacy. Awards include the Annual Teaching Contribution Award and Senior Teaching Supervisor titles at Wenzhou Medical University. He has secured grants such as the University of Essex Postgraduate Research Student Proficio Scheme (2022) and Wenzhou Social Science Association Research Program (2020). Professional activities include teaching Researching Social Life I (SC101) and participation in summer schools like the MIT Sloan Medici Program (2023) and Manchester's Creative Qualitative Methods (2022).

Qifeng LiView profile

Associate Professor

• Convex Optimization
• Nonlinear Systems
• Power and Energy Systems
• +6 more

Qifeng Li is an Associate Professor at the University of Central Florida specializing in Electrical Engineering with a focus on power and energy systems. His research integrates convex optimization and nonlinear dynamics to address challenges in renewable energy integration, microgrid stability, and energy-water-hydrogen nexus systems. Research Interests: Convex optimization, nonlinear systems, grid resilience, energy-water-food nexus Grants: NSF and DOE projects on microgrid stability and cross-system coordination Professional Roles: Editor for CSEE Journal, IEEE Battery Energy Storage Work Group member Honors: China National Scholarship 2012 His recent publications emphasize data-driven optimization methods, voltage stability analysis, and machine learning applications in power systems. Key trends include hybrid physics-data-driven models, stochastic disturbance analysis, and real-time grid control solutions. Scientific Awards: China National Scholarship (2012)

Dylan Hadfield-MenellView profile

Assistant Professor

• AI Alignment
• Human-AI Interaction
• Reinforcement Learning
• +3 more

Dylan Hadfield-Menell is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology, holding the Bonnie and Marty (1964) Tenenbaum Career Development Professorship. His research focuses on AI alignment and human-AI interaction within MIT's School of Engineering. His research interests center on agent alignment problems in AI systems, particularly examining uncertainty in objective optimization for human-robot teams and societal oversight of machine learning systems. Key areas include the principal-agent alignment problem , assistance games frameworks , and robust preference learning that accounts for hidden contextual factors in reinforcement learning from human feedback. His recent publications reveal strong trends toward multi-agent cooperation , formal contract mechanisms for resolving social dilemmas, and advanced evaluation methodologies for AI safety. The research spans theoretical frameworks like open-universe assistance games while addressing practical challenges in language model alignment and cultural bias assessment. Scientific awards include: AI2050 Early Career Fellowship from Schmidt Futures Berkeley Fellowship NSF Graduate Research Fellowship C.V. Ramamoorthy Distinguished Research Award His work bridges theoretical computer science with real-world AI governance challenges, as demonstrated through MIT's participation in AI policy white papers. Current research directions include developing frameworks for transparent AI systems and addressing fundamental limitations in aligning recommender systems with human values through interdisciplinary synthesis.

Andrew D. WhiteView profile

Associate Professor

• Large language models
• Deep learning in chemistry
• Molecular dynamics
• +5 more

Andrew D. White is an Associate Professor of Chemical Engineering at the Hajim School of Engineering & Applied Sciences, University of Rochester. He holds a PhD from the University of Washington (2013). His research focuses on automating scientific discovery through AI, particularly leveraging large language models (LLMs) and deep learning techniques in chemistry. His lab develops agents that integrate literature analysis, hypothesis generation, and experimental design to advance fields like molecular dynamics and drug discovery. Education: PhD in Chemical Engineering, University of Washington, 2013 BS/MS (not explicitly stated in text, inferred from career timeline) Research Interests: Large language models for scientific automation Deep learning applications in chemistry and materials science Molecular dynamics simulations Scientific agents and autonomous systems Publications: His work includes groundbreaking studies on closed-loop AI systems for chemistry, federated learning in molecular property prediction, and multi-agent systems for drug discovery. Recent highlights include the Robin system and ChemCrow tools. Awards: Recipient of the NSF Career Award (2018), NIH Outstanding Investigator Award (2020), and the Curtis Teaching Award (2019). He also advises biotech companies and serves on the National Academy of Sciences' Chemical Sciences Roundtable. Grants & Funding: Supported by DOE, NSF (multiple grants including CBET-1751471), NIH (R35GM137966), and LLNL projects. Collaborates with institutions like Argonne National Lab and Qubit Pharmaceuticals. Labs & Teams: Leads the White Lab at Rochester and co-founded FutureHouse, a nonprofit advancing AI-driven scientific discovery. Supervises a multidisciplinary team of PhD students and postdocs in computational chemistry, AI, and biophysics.

Shani OrgadView profile

Professor

• Gender Studies
• Feminism and Media
• Media Representations
• +7 more

Professor Shani Orgad is a leading academic in the Department of Media and Communications at the London School of Economics (LSE), where she holds the rank of Professor. Her research focuses on gender, feminism, media representations, and globalization, with notable works exploring motherhood, work-life balance, and the intersection of media with contemporary cultural narratives. Education: Orgad earned a bachelor’s degree in Media and Communications from The Hebrew University in Jerusalem, followed by a Master's and PhD in Media and Communications at LSE. She is renowned for her interdisciplinary approach, blending media studies with ethnographic research and sociocultural analysis. Research Interests: Her work critically examines media discourses around gender, motherhood, and inequality. Key themes include the 'confidence culture' critique, menopause visibility, and the role of media in shaping public perceptions of marginalized groups. She has also explored humanitarian communication and the challenges faced by NGOs in engaging the public. Awards: Orgad has been recognized for her teaching excellence, including the 2019 LSE Teaching Excellence Prize and the 2018 LSE Excellence in Education Award. Her book Confidence Culture (2022), co-authored with Rosalind Gill, challenges neoliberal individualism in modern feminist discourse. Public Engagement: She frequently contributes to public discussions on media and gender through blogs, podcasts, and media commentaries. Her work bridges academic rigor with societal relevance, addressing issues like pandemic resilience, menopause discourse, and the impact of social media on self-perception. Current Projects: During the 2024/25 academic year, Orgad is on research leave, focusing on new projects that continue her exploration of media, gender, and cultural dynamics.

Zaur GasimovView profile

Lecturer

• Eastern European History
• Russian-Turkish Relations
• Nationalism and Transnationalism
• +3 more

Zaur Gasimov is a Lecturer at Johannes Gutenberg University Mainz and currently serves as DAAD Departmental Coordinator and Co-Head at the Faculty of Economics and Administrative Sciences, Turkish-German University. He holds a habilitation in Modern History and Eastern European History, with a focus on Eastern European History, political science, and sociology. Education : B.A. in International Relations from Baku State University; M.A. from Catholic University of Eichstätt-Ingolstadt; Doctorate in Eastern European history Research : Concentrates on Russian-Turkish relations, nationalism in Eastern Europe, cultural transfer processes, and historical narratives. His habilitation thesis analyzed Polish-Turkish anti-Soviet alliances. Publications : Authored monographs on Prometheism, Azerbaijani historiography, and Russification policies. Collaborated on comparative studies of cultural transfer and Ottoman-Russian entanglements.

• Statistics
• Public Health
• Medicine
• +11 more

Zhiling Gu is a Research Fellow at Yale School of Public Health, having earned her Ph.D. in Statistics at Iowa State University. Her work integrates statistical theory with applications in public health and medicine. Her research spans Functional Data Analysis Network Analysis Spatiotemporal Modeling Statistical AI Foundations Nonparametric Learning applied to neuroimaging, electronic health records, and environmental health studies. Recent publications focus on Adaptive spatiotemporal models Neuroimaging data processing Pandemic forecasting frameworks Environmental exposure modeling with methodological rigor and practical implementation. Scientific achievements include Runner-up in SMI 2023 Student Paper Competition She has taught STAT 305: Engineering Statistics (ISU) STAT 226: Business Statistics Statistical Computing Statistical Learning and actively engages in academic presentations at conferences like SMI 2024 and CMStatistics 2022.

Fiona LeeView profile

Professor

• Organizational Behavior
• Social Psychology
• Cultural Psychology
• +3 more

Fiona Lee is the Arthur F. Thurnau Professor of Psychology at the University of Michigan, with affiliations in Organizational Studies and the Advisory Committee. She holds a Ph.D. from Harvard University. Her research focuses on three core areas: Identity Integration (how individuals navigate multiple identities), Power Dynamics (effects of power on behavior), and Cultural Differences (impact of cultural contexts on organizations and individuals). She teaches courses on Organizational Psychology and Research Methods in Personality/Social Contexts. Lee’s work bridges social psychology and organizational behavior, emphasizing multicultural experiences and adaptation. Her recent studies explore refugee well-being, racial discrimination coping strategies, and the role of family in resettlement processes. Notably, she investigates how cultural identity integration influences creativity, decision-making, and social tolerance. Her publications span cross-cultural communication, biculturalism, and institutional barriers faced by minorities. Lee’s research often combines qualitative and quantitative methods to address real-world challenges in workplace dynamics and global mobility.